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Abstract

A method to non-invasively and quantitatively characterize thick biological tissues by combining both experimental and computational approaches in tissue optical spectroscopy was developed and validated on fifteen porcine articular cartilage (AC) tissue samples. To the best of our knowledge, this study is the first to couple non-invasive reflectance and fluorescence spectroscopic measurements on freshly harvested tissues with Monte Carlo computational modeling of time-resolved propagation of both excitation light and multi-fluorophore emission. For reflectance, quantitative agreement between simulation and experiment was achieved to better than 11%. Fluorescence data and simulations were used to extract the ratio of the absorption coefficients of constituent fluorophores for each measured AC tissue sample. This ratio could be used to monitor relative changes in concentration of the constituent fluorophores over time. The samples studied possessed the complexity and variability not found in artificial tissue-simulating phantoms and serve as a model for future optical molecular sensing studies on tissue engineered constructs intended for use in human therapeutics. An optical technique that could non-invasively and quantitatively assess soft tissue composition or physiologic status would represent a significant advance in tissue engineering. Moreover, the general approach described here for optical characterization should be broadly applicable to quantitative, non-invasive molecular sensing applications in complex, three-dimensional biological tissues.

Spectrally weighted fluorescence emission W(λ) (see text) for two fluorophores in the AC tissue. These spectra were measured on the RFLS for powdered collagen II (blue line) and for 70 µM NADH in DI-H2O (red dashed line). The black dashed lines indicate the spectral position of band-pass filters that were employed for obtaining time-resolved fluorescence measurements from porcine AC samples.

Average, measured (gray, solid line) and simulated (black, triangles) normalized reflectance spectra from porcine AC. The normalization was done by setting reflectance at 540 nm to unity. The model inputs at each indicated wavelength were obtained from integrating sphere measurements. The error bars represent the results of the variations in the optical properties (see Table 1) input to produce the simulations.